gko::stop::ImplicitResidualNorm< ValueType > Class Template Reference

Stopping criterion based on a solver-maintained squared residual-norm estimate \( \rho_k^2 \approx \| r_k \|^2 \). More...

#include <ginkgo/core/stop/residual_norm.hpp>

Inheritance diagram for gko::stop::ImplicitResidualNorm< ValueType >:

Collaboration diagram for gko::stop::ImplicitResidualNorm< ValueType >:

Classes
class	Factory
struct	parameters_type

Public Types
using	ComplexVector = matrix::Dense< to_complex< ValueType > >
using	NormVector = matrix::Dense< remove_complex< ValueType > >
using	Vector = matrix::Dense< ValueType >

Public Member Functions
const parameters_type &	get_parameters () const
Public Member Functions inherited from gko::stop::Criterion
Updater	update ()
	Returns the updater object. More...
bool	check (uint8 stopping_id, bool set_finalized, array< stopping_status > *stop_status, bool *one_changed, const Updater &updater)
	This checks whether convergence was reached for a certain criterion. More...
Public Member Functions inherited from gko::PolymorphicObject
virtual void	validate_data () const
	Throws gko::InvalidData exception if we found the data inside the object does not fulfill certain property up to our knowledge.
PolymorphicObject &	operator= (const PolymorphicObject &)
std::shared_ptr< const Executor >	get_executor () const noexcept
	Returns the Executor of the object. More...
Public Member Functions inherited from gko::log::EnableLogging< PolymorphicObject >
void	add_logger (std::shared_ptr< const Logger > logger) override
void	remove_logger (const Logger *logger) override
void	remove_logger (ptr_param< const Logger > logger)
const std::vector< std::shared_ptr< const Logger > > &	get_loggers () const override
void	clear_loggers () override
Public Member Functions inherited from gko::log::Loggable
void	remove_logger (ptr_param< const Logger > logger)

Static Public Member Functions
static auto	build () -> decltype(Factory ::create())

Detailed Description

template<typename ValueType = default_precision>
class gko::stop::ImplicitResidualNorm< ValueType >

Stopping criterion based on a solver-maintained squared residual-norm estimate \( \rho_k^2 \approx \| r_k \|^2 \).

Several Krylov methods (CG, BiCGSTAB, …) already compute this quantity per iteration as a by-product of their inner-product recurrences, so the criterion can check convergence without computing a norm of its own — saving the global reduction the explicit ResidualNorm form needs when the solver only passes \( r_k \). The iteration halts once \( \rho_k \le \tau \cdot \beta \), with the same reduction_factor and baseline factory parameters as ResidualNorm:

• mode::rhs_norm (default) — \( \rho_k \le \tau \| b \| \).
• mode::initial_resnorm — \( \rho_k \le \tau \| r_0 \| \).
• mode::absolute — \( \rho_k \le \tau \).

Because \( \rho_k^2 \) is updated by short recurrences rather than recomputed from \( b - A x_k \) each step, it can drift from the true residual norm on long runs in finite precision; pair this criterion with an Iteration cap when that matters.

Note

The solver must pass the squared estimate through Updater::implicit_sq_residual_norm on every check — there is no fallback path. If it is missing, ::gko::NotSupported() is thrown at check time.

Baseline prerequisites at construction time mirror ResidualNorm:

• mode::rhs_norm requires \( b \).
• mode::initial_resnorm requires either \( r_0 \) explicitly or the triple \( (A, b, x_0) \) to derive it.
• mode::absolute requires \( b \) for sizing the per-RHS baseline. If the required arguments are missing, ::gko::NotSupported() is thrown.

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The documentation for this class was generated from the following file:

• ginkgo/core/stop/residual_norm.hpp